guanaco/CHANGELOG.md

Changelog

All notable changes to Guanaco will be documented in this file.

The format is based on Keep a Changelog, and this project adheres to Semantic Versioning.

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[0.5.1] - 2026-06-10

Fixed

• Updater now stashes + hard-resets instead of merge-pulling. Previously if the working tree had any local modifications (e.g. leftover version-string edits from a prior partial update), git pull would abort with a merge conflict and the update silently failed, leaving the old code running. The updater now unconditionally stashes any local changes (including untracked files) and resets to origin/{branch} before reinstalling. This makes the Apply Update button work reliably on every install, even if the repo is dirty.

Changed

• Bumped version to 0.5.1 to ensure existing 0.4.2 → 0.5.x update paths hit the new updater logic immediately.

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[0.5.0] - 2026-06-10

Major Release — Usage Tracking, ROI Dashboard, and Multi-Account Infrastructure

This release represents a significant milestone: Guanaco now tracks every token accurately, displays real cost analytics via a web dashboard, rotates multiple Ollama Cloud accounts, and scrapes live usage tiers from ollama.com instead of guessing.

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New Features

Token Estimation & Accurate Usage Tracking

• skimtoken estimation fallback (analytics.py): When the upstream API (OpenRouter, Ollama Cloud) omits usage data in the response, Guanaco now falls back to skimtoken for token estimation instead of logging zero tokens. Estimates are ~15% accurate — dramatically better than silently losing usage data.
• Proper total_tokens calculation: Fixed total_tokens = prompt_tokens + completion_tokens in analytics logging. Previously some code paths double-counted or omitted totals.
• fallback_reason audit column: Added to request_log schema. When token estimation is used instead of API-reported usage, the reason is recorded (e.g. "api_omitted_usage", "stream_missing_usage") for later audit.
• Input cache-read pricing (roi.py): Tracks input_cache_read tokens separately from input_cache_write, applying the correct Ollama Cloud discount rate (typically 0.25× of input price for cache hits).

ROI Dashboard & Per-Model Analytics

• Web dashboard (dashboard/): New FastAPI-mounted dashboard at /dashboard/ showing:
  • Total tokens consumed (last 24h, 7d, 30d, all-time)
  • Per-model token distribution with visual bars
  • Cost estimates in USD using live OpenRouter pricing
  • ROI configuration panel: Slider for cache_hit_pct (default 70%), editable price multipliers per model
  • Per-model value scoring: Each model gets a "value score" based on (capability / cost) ratio, helping users pick the cheapest model for a given task
• OpenRouter price fetcher (roi.py): Scrapes current model pricing from https://openrouter.ai/api/v1/models with 24h caching. Falls back to hardcoded prices if fetch fails.
• Cache-hit discount logic: ROI calculations apply the user-configured cache_hit_pct to reduce effective input costs, reflecting real-world Ollama Cloud behavior where repeated prompts are cached.

Real Usage-Level Scraping from ollama.com

• _fetch_usage_level_sync() (client.py): New synchronous HTML scraper that parses ollama.com/library/{model} pages to determine actual GPU usage tiers:
  • Handles top-level model badges (x-test-model-cost-slot-active) for unified-tier models
  • Handles per-tag listings (x-test-model-tag-cost + x-test-model-tag-usage-slot-active) for models with multiple size variants
  • Returns usage level 1-4, which maps to multiplier 0.25×, 0.50×, 0.75×, 1.00×
• fetch_usage_levels(): Async parallel fetcher with 1-hour global cache. Fetches all library pages concurrently using asyncio.gather() with thread-pool execution for the blocking HTTP requests.
• Wired into API responses: Both /v1/models (OpenAI-compatible) and /api/ollama/models (internal) now return usage_multiplier and usage_level fields based on scraped live data.
• Fixes major heuristic errors:
  • gemma3:4b and gemma3:12b: was 1.00×, now correctly 0.25× (1 slot)
  • gemma3:27b: was 1.00×, now correctly 0.50× (2 slots)
  • ministral-3: was 0.75×, now correctly 0.25× (1 slot)
  • qwen3-vl: stays 0.75× (3 slots) — heuristic accidentally got this one right
  • deepseek-v4-pro: stays 1.00× (4 slots)

Multi-Account Ollama Cloud Rotation

• accounts.py: New module managing multiple Ollama Cloud accounts:
  • Each account has its own API key + session cookie
  • Load-balanced request routing based on usage and subscription tier
  • Quota-aware selection: least-loaded accounts preferred; new/untested accounts get priority for immediate validation
• Premium model routing: Models kimi-k2.6 and glm-5.1 restricted to Pro/Max accounts only. Free-tier accounts are skipped for these models.
• Per-account usage tracking: Analytics DB records which account handled each request, enabling per-account cost breakdowns.

Model Catalog Expansion

• Added minimax-m3 (new MiniMax flagship)
• Added nemotron-3-ultra (NVIDIA enterprise model)
• Added kimi-k2.6 with 200k context window support

Web Search / Scrape Emulation

• Search provider plugins (search/providers/): Modular search backend support:
  • Brave Search API
  • Cohere RAG API
  • Exa (formerly Metaphor)
  • Firecrawl (web scraping)
  • Jina AI (neural search)
  • SearXNG (self-hosted meta-search)
  • Serper (Google Search API)
  • Tavily (AI-native search)
• Search router (search/base.py): Unified interface — Guanaco presents a single /search endpoint regardless of which provider is configured.

Fixes

Config & Install Robustness

• Missing UsageConfig fields: Added last_plan, redirect_on_full, last_session_reset, last_weekly_reset, last_checked to prevent AttributeError crashes on configs from v0.4.2 and earlier.
• Config migration layer: load_config() now auto-migrates v0.4.2 configs to v0.4.3+ schema on first load. No manual intervention needed.
• Package rename: Renamed PyPI package from guanaco → guanaco-llm-proxy to avoid collision with an existing guanaco package on PyPI.
• Install script fixes (install.sh):
  • Ollama API key validation now uses the correct env var name
  • Fixed .env file write pattern (was writing malformed key=value pairs)
  • Fixed grep pattern for detecting existing config
• Startup version sanity check: Detects repo/venv version mismatch on boot and logs a warning. Prevents confusing "why is /health showing the old version?" issues.
• systemd service: Fixed WorkingDirectory to point at the actual repo checkout. Added GUANACO_CONFIG_DIR env var to service file.

Dashboard & Analytics Fixes

• Removed broken usage_multiplier column: The analytics DB no longer tracks usage_multiplier per request (it was always wrong due to heuristic mismatch). Model-level multipliers are now fetched live from ollama.com.
• Backward compat for SearchConfig: Older installs missing search configuration no longer crash on startup.

Infrastructure

CI/CD

• GitHub Actions CI (.github/workflows/ci.yml): Runs on every push — lint, type-check, unit tests.
• GitHub Actions Release (.github/workflows/release.yml): Automated PyPI publish on tag push.

Docker

• Dockerfile.test: Containerized smoke-test environment for CI.
• test-local.sh: One-command local smoke test — builds Docker image, starts server, hits /health, validates version string.

Project Hygiene

• Added CODE_OF_CONDUCT.md, CONTRIBUTING.md, LICENSE (MIT)
• Added .gitignore with Python/venv patterns
• Added macOS launch agent plist (com.guanaco.start.plist)
• Added systemd service templates (guanaco.service, oct.service)

API Changes

Added Fields

• /v1/models response now includes:
  • usage_multiplier (float): cost multiplier 0.25-1.00
  • usage_level (int): raw level 1-4, 0 = unknown
• /api/ollama/models response now includes:
  • usage_multiplier (float)
  • usage_level (int)

Schema Changes

• request_log table: added fallback_reason TEXT column
• request_log table: removed usage_multiplier column (was unreliable)
• New roi_config table: stores cache_hit_pct, price_multiplier, per-model overrides

Performance

• Parallel library scraping: All ollama.com library pages are fetched concurrently. For a catalog of ~50 models, total scrape time is ~3-5 seconds vs. ~60 seconds sequential.
• 1-hour cache: Scraped usage levels are cached globally, so the 3-5 second penalty only hits once per hour.
• ROI price cache: OpenRouter prices cached for 24 hours. Dashboard loads instantly after first visit.

Deprecated / Removed

• Heuristic _get_model_multiplier(): Still exists as fallback when ollama.com scraping fails, but is no longer the primary source. Returns 0.25 for ≤8B, 0.50 for ≤70B, 0.75 for ≤200B, 1.00 for larger.
• usage_multiplier column in analytics DB: Dropped. Use /v1/models or /api/ollama/models to get live multipliers.

Known Issues

• Dev server restart unreliable on isolated instance: The uvicorn process sometimes starts without producing logs. Production (systemctl restart guanaco.service) is unaffected.
• Library scraper depends on ollama.com DOM: If ollama.com changes their HTML test attributes (x-test-model-*), the scraper will fall back to heuristic. Monitor /api/ollama/models for sudden multiplier shifts.

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[0.4.2] - 2026-05-15

New Features

• Multi-account Ollama Cloud rotation with quota-aware selection
• Premium model routing (kimi-k2.6, glm-5.1 → Pro/Max only)
• Per-account usage tracking

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[0.4.1] - 2026-05-01

Fixes

• Rate-limit retry logic for Ollama Cloud 429 responses
• SSE streaming stability improvements

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[0.4.0] - 2026-04-20

New Features

• Initial Ollama Cloud proxy support
• OpenAI-compatible /v1/chat/completions endpoint
• Token usage tracking with SQLite analytics DB
• Basic web dashboard

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[0.3.9] and earlier

See GitHub releases for earlier versions.